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add Dockerfile, an onstart.sh and some post build steps
Add a post-build script that runs the first time you execute it on a machine with a GPU, since some stuff won't build in the builder
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.git | ||
.env | ||
*.pyc | ||
Dockerfile |
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FROM pytorch/pytorch:2.4.0-cuda12.4-cudnn9-devel AS builder | ||
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# Install build dependencies | ||
RUN apt-get update && \ | ||
apt-get install -y ffmpeg build-essential git rdfind | ||
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WORKDIR /app | ||
ADD trellis /app/trellis | ||
ADD setup.sh /app/setup.sh | ||
ADD app.py /app/app.py | ||
ADD example.py /app/example.py | ||
ADD extensions /app/extensions | ||
ADD assets /app/assets | ||
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# Setup conda | ||
RUN conda config --set always_yes true && \ | ||
conda init && \ | ||
conda config --add channels defaults | ||
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# Use bash shell so we can source activate | ||
SHELL ["/bin/bash", "-c"] | ||
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RUN conda install torchvision=0.19.0 \ | ||
onnx==1.17.0 \ | ||
pytorch=2.4.0 \ | ||
pytorch-cuda=12.4 \ | ||
--force-reinstall \ | ||
-c pytorch \ | ||
-c nvidia | ||
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# Create a g++ wrapper for JIT, since the include dirs are passed with -i rather than -I for some reason | ||
RUN printf '#!/usr/bin/env bash\nexec /usr/bin/g++ -I/usr/local/cuda/include -I/usr/local/cuda/include/crt "$@"\n' > /usr/local/bin/gxx-wrapper && \ | ||
chmod +x /usr/local/bin/gxx-wrapper | ||
ENV CXX=/usr/local/bin/gxx-wrapper | ||
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# Run setup.sh - this won't install all the things due to missing GPU in the builder | ||
RUN conda run -n base ./setup.sh --basic --xformers --flash-attn --diffoctreerast --vox2seq --spconv --mipgaussian --kaolin --nvdiffrast --demo | ||
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# Now install additional Python packages | ||
# These ones work inside the builder | ||
RUN conda run -n base pip install diso | ||
RUN conda run -n base pip install plyfile utils3d flash_attn spconv-cu120 xformers onnxscript | ||
RUN conda run -n base pip install kaolin -f https://nvidia-kaolin.s3.us-east-2.amazonaws.com/torch-2.4.0_cu121.html | ||
RUN conda run -n base pip install git+https://github.com/NVlabs/nvdiffrast.git | ||
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# Remove downloaded packages from conda and pip | ||
RUN conda clean --all -f -y | ||
RUN pip cache purge | ||
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# Deduplicate with rdfind | ||
# This reduces the size of the image by a few hundred megs. | ||
RUN rdfind -makesymlinks true /opt/conda | ||
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# Final stage | ||
FROM pytorch/pytorch:2.4.0-cuda12.4-cudnn9-devel AS final | ||
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WORKDIR /app | ||
COPY --from=builder /usr/local/bin/gxx-wrapper /usr/local/bin/gxx-wrapper | ||
COPY --from=builder /opt/conda /opt/conda | ||
COPY --from=builder /root /root | ||
COPY --from=builder /app /app | ||
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# Reinstall any runtime tools needed | ||
# git and build-essential are needed for post_install.sh script. | ||
# vim and strace are useful for debugging, remove those if you want to. | ||
RUN apt-get update && \ | ||
apt-get install -y build-essential \ | ||
git \ | ||
strace \ | ||
vim && \ | ||
rm -rf /var/lib/apt/lists/* | ||
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# install these last, so we can experiment without excessive build times. | ||
COPY onstart.sh /app/onstart.sh | ||
COPY post_install.sh /app/post_install.sh | ||
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ENV PATH=/opt/conda/bin:$PATH | ||
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# This script runs the post_install steps | ||
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# If you're pushing to a container registry, let this run once, run some | ||
# tests, then do `docker commit` to save the models along with the image. | ||
# This will ensure that it won't fail at runtime due to models being | ||
# unavailable, or network restrictions. | ||
CMD ["/app/onstart.sh"] | ||
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#!/bin/bash | ||
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cd /app | ||
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echo "Doing post install steps" | ||
./post_install.sh | ||
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export CXX=/usr/local/bin/gxx-wrapper | ||
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echo "Launching app" | ||
python3 app.py | ||
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#!/bin/bash | ||
set -e | ||
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# Check if post-install steps have already been run | ||
if [ -f /app/.post_install_done ]; then | ||
echo "Post-install steps already completed." | ||
exit 0 | ||
fi | ||
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cd /app | ||
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echo "Install stuff that couldn't be installed without GPU" | ||
# Run the demo setup | ||
conda run -n base ./setup.sh --mipgaussian --diffoctreerast | ||
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echo "Proving it actually works..." | ||
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export CXX=/usr/local/bin/gxx-wrapper | ||
python example.py | ||
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# Mark completion | ||
touch /app/.post_install_done | ||
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echo "Post-install steps completed successfully." | ||
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